Winning NFL Betting with KNIME, Wind Data and Regression Analysis - Dennis Ganzaroli su Low Code for Data Science

Last time we saw that we could use logistic regression to estimate team ratings based on past results and some extra indicators such as rest days and whether it was a divisional game or not.

Furthermore, the additional consideration of wind speed led to a significant improvement of the model. The model improved by 5 percentage points.

The full article can be found here: Who is the best team in the NFL? (https://medium.com/low-code-for-advanced-data-science/who-is-the-best-team-in-the-nfl-b9724cd3deee)

The downside of this additional indicator was that we could not (yet) use it for predictions, as we did not yet have any forecast data available for the weather data. Moreover, the data from nfldata lacked values that we imputed using the mean value of the wind speed.

For that reason, this time we will be looking at the automatic collection of wind speed data.

Read more: https://medium.com/low-code-for-advanced-data-science/winning-nfl-betting-with-knime-wind-data-and-regression-analysis-0535db8e0d1a

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